Low Earth Orbit (LEO) constellations and Unmanned Aerial Vehicle (UAV) networks enable wide coverage for the sixth generation (6 G) mobile communication. However, it is a challenge to achieve high scheduling success rate, ultra-low latency, and efficient load balance in the Space-Air-Ground Integrated 6 G Network (SAGGIN). This paper addresses the following issue:How to effectively and orderly transmit time-sensitive traffic in SAGGIN under strict deadlines, limited computational ability, and restrained link capacity?Specifically, this paper uses Software-Defined Networking (SDN) and designs a joint optimization method to enhance the traffic transmission ability of SAGGIN. Considering response time, computing cost, and link capacity in SAGGIN, the scheduling, computing, and load balance issues are modeled as a multi-objective optimization problem that minimizes the worst-case response time and computing cost of data frames while maximizing the network flow. Then, this paper leverages a Federated Reinforcement Learning (FRL) scheme to solve the problem. Results show that the FRL could achieve great scheduling, computing, and load balance performance. Specifically, our method can successfully schedule 80% of the traffic at most when the current network load is around 90%. Furthermore, the computational delay could reduce around 50%.

Among the three 5G scenarios identified by ITU-R, massive MTC poses very challenging uplink design target which requires the simultaneous support of enhanced coverage, long battery life and massive connection density. During the 5G Release 14 study phase in 3GPP, the working group studied the Non-Orthogonal Multiple Access (NOMA) scheme which can improve link budget and increase user density with the cost of complex user detection scheme. Among all the candidates, Resource Spread Multiple Access (RSMA) scheme shows promising performance gain without introducing too much complexity on the receiver design. In this paper, we briefly review the RSMA scheme. For the link level performance analysis, we firstly analyze and compare the link budget among RSMA, TDMA, and FDMA to find where the gain for RSMA comes from. Meanwhile, we provide preliminary results to justify the gains compared with OMA scheme. On system design, we review the whole procedure and propose to use user centric mobility and grant free to improve the system efficiency along with NOMA.

In heterogeneous networks, low power nodes may be deployed within macro cells for coverage and capacity improvement. Due to transmit power difference between low power nodes and macro cells, downlink (DL) and uplink (UL) coverage of the low power nodes can be very different. This DL-UL coverage difference could negatively affect system performance on both the DL and the UL. We describe a few techniques to alleviate this problem in HSPA. We present simulation results to show the effectiveness of these techniques as well as the system performance improvement of heterogeneous networks over traditional macro cell only deployments in HSPA.

Heterogeneous networks (HetNets), consisting of Macro NodeBs (macros) and low power Pico NodeBs (picos), can increase system capacity by offloading some users to the picos. However, this offloading may be limited due to intercell interference from macros to picos that reduces their coverage. HSPA Multi-carrier HetNets allow the use of range expansion techniques to achieve more offloading, such as power reduction from the macros on one carrier. This paper provides a system level analysis of the gain provided by power reduction on one carrier of the macros in a HetNet environment. As the interference from the macros is reduced, more capacity offloading to picos occurs and higher system capacity can be achieved. By considering cell biasing in serving cell selection, further gains can be observed.

Multiple Input Multiple Output (MIMO) transmission improves downlink spectral efficiency and is a key feature of Release 7 High Speed Downlink Packet Access (HSDPA). When the Node-B is configured in the MIMO mode with secondary common control pilot channel (S-CPICH), the power amplifiers (PAs) for the two transmit antennas are not balanced. A common pre-coder is required to balance the PAs for legacy and dual-stream MIMO transmissions. In addition, codebook restriction is needed to balance the PAs for single-stream MIMO transmissions. Despite codebook restriction, MIMO performance degradation is small. Legacy user performance in a MIMO cell suffers due to power and interference penalties associated with the Secondary Common Pilot Channel (S-CPICH). By reducing the S-CPICH transmit power, this degradation can be reduced, without significantly compromising the channel estimation quality for MIMO users in the cell.

Higher Order Modulation (HOM, 64-QAM) and Multiple Input Multiple Output (MIMO) transmissions are two key features introduced in the Release 7 (HSPA+) WCDMA systems to improve downlink performance. This paper focuses on the performance analysis of 64-QAM and MIMO in the WCDMA system. We describe the equalizer design for supporting these features as well as the simulation results demonstrating the higher system throughput and better user experience provided by these features.

We analyze the performance of voice services over 3GPP WCDMA networks for Release 99 and Release 7 deployments. We show, by using simulations, that the system capacity of Release 7 VoIP is significantly higher than the Release 99 circuit-switched voice under similar system conditions and voice quality. These results are obtained under the 3GPP simulation assumptions where uplink and downlink constraints for power, code and interference are considered. Both AMR 12.2 and 5.9 as well as different types of mobile receivers (Rake and equalizer, single and dual receive antennas) are considered. We also show that the capacity and performance can be increased significantly further by using uplink interference cancellation at the base station. The performance of best effort traffic in the presence of voice users is also analyzed.

This work investigates the design of linear precoders for ARQ packet retransmissions in multi-input multi-output (MIMO) systems. We consider transmitter precoder design based on partial MIMO channel information in the form of their covariance feedback. Our objective is to maximize the ergodic mutual information provided by multiple (re)transmissions of a packet subject to transmission power constraint. We propose a set of near-optimal successive linear ARQ precoders for flat fading MIMO channels. This progressive linear ARQ precoder combines the appropriate power loading and the reverse-order pairing of singular values in the current retransmission with previous transmissions. This reverse-order pairing is a special feature unique to our sequential ARQ preceding approach with demonstrated performance gains.

We investigate the joint optimization of automatic repeat request (ARQ) and MIMO diversity for multi-user wireless communication systems. Exploiting MIMO for diversity gain and ARQ for error correction, our goal is to better integrate MIMO and ARQ in the transceivers to improve multi-user uplink performance. Specifically, we design optimal linear precoders for ARQ retransmissions by multiple wireless uplink terminals equipped with MIMO transmitters and we rely on joint detection of multiple retransmissions at the receivers. To better utilize ARQ diversity, we derive a set of progressive linear ARQ precoders for flat fading multiple-access channels based on the criterion of maximizing the mutual information of multiuser (re)-transmissions. We propose two efficient iterative numerical algorithms to determine the optimal precoders.

We investigate the design of optimal linear transceiver for multi-input-multi-output (MIMO) systems under channel mean feedback. We consider the case in which the receiver has perfect channel knowledge while the transmitter has only mean and variance information of the channel coefficients. We aim to minimize the mean square error of symbol detection by jointly designing the transmitter linear precoder and the receiver linear decoder. We present the optimal transceiver structure for any rank of channel mean matrix together with the sufficient and necessary conditions for optimal power loading. Furthermore, we provide a numerical optimal power loading strategy using water-filling principle, as well as one sub-optimal solution based on Jensen's inequality.

This work investigates the design of robust precoders for ARQ packet retransmissions in Multi-Input Multi-Output (MIMO) systems under channel uncertainty. In practice, it is common for transmitters to only have imperfect Channel State Information (CSI). More specifically the channel uncertainty is characterized by the Frobenius norm between the actual and estimated channel. Given a known bound on the channel knowledge error, our objective is to sequentially design the robust precoder for each (re)-transmission that minimizes the Mean Square Error (MSE) for the worst case channel within CSI error bound. This min-max problem is solved by Lagrangian optimization. The robust precoders are proposed in this paper with simulation results demonstrating the worst case performance gain.

This paper investigates the optimal linear precoder design for packet retransmissions in multi-input-multi-output (MIMO) systems. To fully utilize the time diversity provided by automatic repeat request (ARQ), we derive a sequence of successive optimal linear ARQ precoders for flat fading MIMO channels, which minimize the mean-square error between the transmitted data and the joint receiver output. The optimization is subject to an overall transmit power constraint. This progressive linear ARQ precoder combines the appropriate power loading and the optimal pairing of channel matrix singular values in the current retransmission with previous transmissions. This optimal pairing is a special feature unique to our sequential ARQ precoding approach. Simulation results demonstrate the effectiveness of this optimized ARQ precoding in reducing symbol MSE and detection bit-error rate.

The paper presents a method for enhancing wireless ARQ system performance by combining packet retransmissions through frequency-selective channels. As a measure of system performance, we derive the total mutual information (or channel capacity) provided by multiple transmissions of a packet through different channels. Retransmissions are uniquely linear precoded and/or truncated in relation to the original transmission. With the objective of maximizing total throughput, optimal linear precoders are developed for zero-padded packet transmissions. These precoders effectively implement power loading with the right singular vectors of the original transmission channel serving as basis vectors. Simulation results validate the increase in the overall mutual information and throughput from optimized precoding.

The paper investigates the constrained capacity of sequential ARQ linear precoding in flat fading MIMO systems. To utilize fully the time diversity provided by ARQ, we derive the optimal linear ARQ precoders in a flat fading MIMO channel with the objective of maximizing the mutual information delivered by multiple transmissions of the same packet. The capacity-maximizing ARQ precoders combine water-pouring power loading and the optimal pairing of singular vectors in the current retransmission with those from previous transmissions. This optimal pairing is a special feature unique to sequential ARQ precoding and plays important role in maximizing the mutual information.

This paper addresses the problem of efficient and robust transmission of video over a hierarchical wireless infrastructure. First, we compress the data generated by the video sources using a multi-resolution wavelet coder. Subsequently, the generated bitstreams are transmitted over a wireless infrastructure to multiple regional processing centers (RPC), which then send the distorted bitstreams to a common higher-level processing center/receiver. We propose a symmetric framework for the joint compression and error protection of the correlated video bitstreams received by the RPC. We show that significantly improved video performance can be obtained by our framework over a variety of channel conditions.